In vivo effects of mutant RHOA on tumor formation in an orthotopic inoculation model

Nishizawa,Takashi; Nakano,Kiyotaka; Fujii,Etsuko; Komura,Daisuke; Kuroiwa,Yoshie; Ishimaru,Chisako; Monnai,Makoto; Aburatani,Hiroyuki; Ishikawa,Shumpei; Suzuki,Masami

doi:10.3892/or.2019.7300

In vivo effects of mutant RHOA on tumor formation in an orthotopic inoculation model

Authors:
- Takashi Nishizawa
- Kiyotaka Nakano
- Etsuko Fujii
- Daisuke Komura
- Yoshie Kuroiwa
- Chisako Ishimaru
- Makoto Monnai
- Hiroyuki Aburatani
- Shumpei Ishikawa
- Masami Suzuki
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Affiliations: Department of Research, Forerunner Pharma Research Co., Ltd., Komaba Open Laboratory, The University of Tokyo, Tokyo 153‑8904, Japan, Department of Genomic Pathology, Medical Research Institute, Tokyo Medical and Dental University, Tokyo 113‑8510, Japan, Chugai Research Institute for Medical Science Co., Ltd., Kamakura, Kanagawa 247‑8530, Japan, Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153‑8904, Japan
Published online on: September 3, 2019 https://doi.org/10.3892/or.2019.7300
Pages: 1745-1754
Copyright : © Nishizawa et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY 4.0].

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Abstract

Ras homolog family member A (RHOA) mutations are driver genes in diffuse‑type gastric cancers (DGCs), and we previously revealed that RHOA mutations contribute to cancer cell survival and cell migration through their dominant negative effect on Rho‑associated kinase (ROCK) signaling in vitro. However, how RHOA mutations contribute to DGC development in vivo is poorly understood. In the present study, the contribution of RHOA mutations to tumor morphology was investigated using an orthotopic xenograft model using the gastric cancer cell line MKN74, in which wild‑type (WT) or mutated (Y42C and Y42S) RHOA had been introduced. When we conducted RNA sequencing to distinguish between the genes expressed in human tumor tissues from those in mouse stroma, the expression profiles of the tumors were clearly divided into a Y42C/Y42S group and a mock/WT group. Through gene set enrichment analysis, it was revealed that inflammation‑ and hypoxia‑related pathways were enriched in the mock/WT tumors; however, cell metabolism‑ and cell cycle‑related pathways such as Myc, E2F, oxidative phosphorylation and G2M checkpoint were enriched in the Y42C/Y42S tumors. In addition, the gene set related to ROCK signaling inhibition was enriched in the RHOA‑mutated group, which indicated that a series of events are related to ROCK inhibition induced by RHOA mutations. Histopathological analysis revealed that small tumor nests were more frequent in RHOA mutants than in the mock or WT group. In addition, increased blood vessel formation and infiltration of macrophages within the tumor mass were observed in the RHOA mutants. Furthermore, unlike mock/WT, the RHOA‑mutated tumor cells had little antitumor host reaction in the invasive front, which is similar to the pattern of mucosal invasion in clinical RHOA‑mutated DGC. These transcriptome and pathological analyses revealed that mutated RHOA functionally contributes to the acquisition of DGC features, which will accelerate our understanding of the contribution of RHOA mutations in DGC biology and the development of further therapeutic strategies.

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1	Ma J, Shen H, Kapesa L and Zeng S: Lauren classification and individualized chemotherapy in gastric cancer. Oncol Lett. 11:2959–2964. 2016. View Article : Google Scholar : PubMed/NCBI
2	Chen YC, Fang WL, Wang RF, Liu CA, Yang MH, Lo SS, Wu CW, Li AF, Shyr YM and Huang KH: Clinicopathological variation of lauren classification in gastric cancer. Pathol Oncol Res. 22:197–202. 2016. View Article : Google Scholar : PubMed/NCBI
3	Chiaravalli AM, Klersy C, Vanoli A, Ferretti A, Capella C and Solcia E: Histotype-based prognostic classification of gastric cancer. World J Gastroenterol. 18:896–904. 2012. View Article : Google Scholar : PubMed/NCBI
4	Kakiuchi M, Nishizawa T, Ueda H, Gotoh K, Tanaka A, Hayashi A, Yamamoto S, Tatsuno K, Katoh H, Watanabe Y, et al: Recurrent gain-of-function mutations of RHOA in diffuse-type gastric carcinoma. Nat Genet. 46:583–587. 2014. View Article : Google Scholar : PubMed/NCBI
5	Wang K, Yuen ST, Xu J, Lee SP, Yan HH, Shi ST, Siu HC, Deng S, Chu KM, Law S, et al: Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat Genet. 46:573–582. 2014. View Article : Google Scholar : PubMed/NCBI
6	Cancer Genome Atlas Research Network, . Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 513:202–209. 2014. View Article : Google Scholar : PubMed/NCBI
7	Ushiku T, Ishikawa S, Kakiuchi M, Tanaka A, Katoh H, Aburatani H, Lauwers GY and Fukayama M: RHOA mutation in diffuse-type gastric cancer: A comparative clinicopathology analysis of 87 cases. Gastric Cancer. 19:403–411. 2016. View Article : Google Scholar : PubMed/NCBI
8	Stankiewicz TR and Linseman DA: Rho family GTPases: Key players in neuronal development, neuronal survival, and neurodegeneration. Front Cell Neurosci. 8:3142014. View Article : Google Scholar : PubMed/NCBI
9	Jaffe AB and Hall A: Rho GTPases: Biochemistry and biology. Annu Rev Cell Dev Biol. 21:247–269. 2005. View Article : Google Scholar : PubMed/NCBI
10	Nishizawa T, Nakano K, Harada A, Kakiuchi M, Funahashi SI, Suzuki M, Ishikawa S and Aburatani H: DGC-specific RHOA mutations maintained cancer cell survival and promoted cell migration via ROCK inactivation. Oncotarget. 9:23198–23207. 2018. View Article : Google Scholar : PubMed/NCBI
11	Céspedes MV, Casanova I, Parreño M and Mangues R: Mouse models in oncogenesis and cancer therapy. Clin Transl Oncol. 8:318–329. 2006. View Article : Google Scholar : PubMed/NCBI
12	Bibby MC: Orthotopic models of cancer for preclinical drug evaluation: Advantages and disadvantages. Eur J Cancer. 40:852–857. 2004. View Article : Google Scholar : PubMed/NCBI
13	Killion JJ, Radinsky R and Fidler IJ: Orthotopic models are necessary to predict therapy of transplantable tumors in mice. Cancer Metastasis Rev. 17:279–284. 1999. View Article : Google Scholar
14	Nakano K, Nishizawa T, Komura D, Fujii E, Monnai M, Kato A, Funahashi SI, Ishikawa S and Suzuki M: Difference in morphology and interactome profiles between orthotopic and subcutaneous gastric cancer xenograft models. J Toxicol Pathol. 31:293–300. 2018. View Article : Google Scholar : PubMed/NCBI
15	Junttila MR and de Sauvage FJ: Influence of tumour micro- environment heterogeneity on therapeutic response. Nature. 501:346–354. 2013. View Article : Google Scholar : PubMed/NCBI
16	Makalowski W, Zhang J and Boguski MS: Comparative analysis of 1196 orthologous mouse and human full-length mRNA and protein sequences. Genome Res. 6:846–857. 1996. View Article : Google Scholar : PubMed/NCBI
17	Bainer R, Frankenberger C, Rabe D, An G, Gilad Y and Rosner MR: Gene expression in local stroma reflects breast tumor states and predicts patient outcome. Sci Rep. 6:392402016. View Article : Google Scholar : PubMed/NCBI
18	Komura D, Isagawa T, Kishi K, Suzuki R, Sato R, Tanaka M, Katoh H, Yamamoto S, Tatsuno K, Fukayama M, et al: CASTIN: A system for comprehensive analysis of cancer-stromal interactome. BMC Genomics. 17:8992016. View Article : Google Scholar : PubMed/NCBI
19	Motoyama T, Hojo H and Watanabe H: Comparison of seven cell lines derived from human gastric carcinomas. Acta Pathol Jpn. 36:65–83. 1986.PubMed/NCBI
20	Busuttil RA, Liu DS, Di Costanzo N, Schröder J, Mitchell C and Boussioutas A: An orthotopic mouse model of gastric cancer invasion and metastasis. Sci Rep. 8:8252018. View Article : Google Scholar : PubMed/NCBI
21	Yanagihara K, Takigahira M, Tanaka H, Komatsu T, Fukumoto H, Koizumi F, Nishio K, Ochiya T, Ino Y and Hirohashi S: Development and biological analysis of peritoneal metastasis mouse models for human scirrhous stomach cancer. Cancer Sci. 96:323–332. 2005. View Article : Google Scholar : PubMed/NCBI
22	Gu Z, Eils R and Schlesner M: Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 32:2847–2849. 2016. View Article : Google Scholar : PubMed/NCBI
23	Langmead B, Trapnell C, Pop M and Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10:R252009. View Article : Google Scholar : PubMed/NCBI
24	Love MI, Huber W and Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15:5502014. View Article : Google Scholar : PubMed/NCBI
25	Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES and Mesirov JP: Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 102:15545–15550. 2005. View Article : Google Scholar : PubMed/NCBI
26	Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstråle M, Laurila E, et al: PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 34:267–273. 2003. View Article : Google Scholar : PubMed/NCBI
27	Chapman S, McDermott DH, Shen K, Jang MK and McBride AA: The effect of Rho kinase inhibition on long-term keratinocyte proliferation is rapid and conditional. Stem Cell Res Ther. 5:602014. View Article : Google Scholar : PubMed/NCBI
28	Suzuki M, Katsuyama K, Adachi K, Ogawa Y, Yorozu K, Fujii E, Misawa Y and Sugimoto T: Combination of fixation using PLP fixative and embedding in paraffin by the AMeX method is useful for histochemical studies in assessment of immunotoxicity. J Toxicol Sci. 27:165–172. 2002. View Article : Google Scholar : PubMed/NCBI
29	Sato Y, Mukai K, Watanabe S, Goto M and Shimosato Y: The AMeX method. A simplified technique of tissue processing and paraffin embedding with improved preservation of antigens for immunostaining. Am J Pathol. 125:431–435. 1986.PubMed/NCBI
30	Corliss BA, Azimi MS, Munson JM, Peirce SM and Murfee WL: Macrophages: An inflammatory link between angiogenesis and lymphangiogenesis. Microcirculation. 23:95–121. 2016. View Article : Google Scholar : PubMed/NCBI
31	Squadrito ML and De Palma M: Macrophage regulation of tumor angiogenesis: Implications for cancer therapy. Mol Aspects Med. 32:123–145. 2011. View Article : Google Scholar : PubMed/NCBI
32	Madeddu C, Gramignano G, Kotsonis P, Coghe F, Atzeni V, Scartozzi M and Macciò A: Microenvironmental M1 tumor-associated macrophage polarization influences cancer-related anemia in advanced ovarian cancer: Key role of interleukin-6. Haematologica. 103:e388–e391. 2018. View Article : Google Scholar : PubMed/NCBI
33	Mantovani A and Allavena P: The interaction of anticancer therapies with tumor-associated macrophages. J Exp Med. 212:435–445. 2015. View Article : Google Scholar : PubMed/NCBI
34	Quatromoni JG and Eruslanov E: Tumor-associated macrophages: Function, phenotype, and link to prognosis in human lung cancer. Am J Transl Res. 4:376–389. 2012.PubMed/NCBI
35	Yin S, Huang J, Li Z, Zhang J, Luo J, Lu C and Xu H and Xu H: The prognostic and clinicopathological significance of tumor-associated macrophages in patients with gastric cancer: A meta-analysis. PLoS One. 12:e01700422017. View Article : Google Scholar : PubMed/NCBI
36	Ohgushi M, Matsumura M, Eiraku M, Murakami K, Aramaki T, Nishiyama A, Muguruma K, Nakano T, Suga H, Ueno M, et al: Molecular pathway and cell state responsible for dissociation-induced apoptosis in human pluripotent stem cells. Cell Stem Cell. 7:225–239. 2010. View Article : Google Scholar : PubMed/NCBI
37	Chung W, Eum HH, Lee HO, Lee KM, Lee HB, Kim KT, Ryu HS, Kim S, Lee JE, Park YH, et al: Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nat Commun. 8:150812017. View Article : Google Scholar : PubMed/NCBI
38	Azizi E, Carr AJ, Plitas G, Cornish AE, Konopacki C, Prabhakaran S, Nainys J, Wu K, Kiseliovas V, Setty M, et al: Single-cell map of diverse immune phenotypes in the breast tumor microenvironment. Cell. 174:1293–1308.e36. 2018. View Article : Google Scholar : PubMed/NCBI
39	Lambrechts D, Wauters E, Boeckx B, Aibar S, Nittner D, Burton O, Bassez A, Decaluwé H, Pircher A, Van den Eynde K, et al: Phenotype molding of stromal cells in the lung tumor microenvironment. Nat Med. 24:1277–1289. 2018. View Article : Google Scholar : PubMed/NCBI